{"id":"https://openalex.org/W7133355960","doi":"https://doi.org/10.48550/arxiv.2603.00500","title":"Zero-Shot Robotic Manipulation via 3D Gaussian Splatting-Enhanced Multimodal Retrieval-Augmented Generation","display_name":"Zero-Shot Robotic Manipulation via 3D Gaussian Splatting-Enhanced Multimodal Retrieval-Augmented Generation","publication_year":2026,"publication_date":"2026-02-28","ids":{"openalex":"https://openalex.org/W7133355960","doi":"https://doi.org/10.48550/arxiv.2603.00500"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.00500","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.00500","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.00500","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084354953","display_name":"Zilong Xie","orcid":"https://orcid.org/0000-0002-6851-7554"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Zilong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074868631","display_name":"Jingyu Gong","orcid":"https://orcid.org/0000-0002-4536-0953"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gong, Jingyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127881091","display_name":"Xin Tan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tan, Xin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128034464","display_name":"Zhizhong Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Zhizhong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5127875308","display_name":"Yuan Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Yuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.7534999847412109,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.7534999847412109,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.17509999871253967,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10709","display_name":"Social Robot Interaction and HRI","score":0.014000000432133675,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6033999919891357},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5430999994277954},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5203999876976013},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.49540001153945923},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.47200000286102295},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.46619999408721924},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.45089998841285706},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.42080000042915344},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.40639999508857727},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.38429999351501465}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7688999772071838},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7364000082015991},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6377000212669373},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6033999919891357},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5430999994277954},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5203999876976013},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.49540001153945923},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47200000286102295},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.46619999408721924},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.45089998841285706},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.42080000042915344},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.40639999508857727},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.38429999351501465},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.34540000557899475},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3368000090122223},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.3257000148296356},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3257000148296356},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.3183000087738037},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.3025999963283539},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.3018999993801117},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.3010999858379364},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.2980000078678131},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2912999987602234},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.28949999809265137},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C120515352","wikidata":"https://www.wikidata.org/wiki/Q2564580","display_name":"Image plane","level":3,"score":0.27090001106262207},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.26669999957084656},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.2651999890804291},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C158096908","wikidata":"https://www.wikidata.org/wiki/Q3983303","display_name":"Template matching","level":3,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.00500","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.00500","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.00500","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.00500","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Existing":[0],"end-to-end":[1],"approaches":[2],"of":[3,136,167,183],"robotic":[4,60,231],"manipulation":[5,67],"often":[6],"lack":[7],"generalization":[8],"to":[9,15,94,140,160,163,195,208,235],"unseen":[10,236],"objects":[11,237],"or":[12],"tasks":[13],"due":[14],"limited":[16],"data":[17],"and":[18,36,77,110,156,204,226],"poor":[19],"interpretability.":[20],"While":[21],"recent":[22],"Multimodal":[23,53,84],"Large":[24],"Language":[25],"Models":[26],"(MLLMs)":[27],"demonstrate":[28],"strong":[29],"commonsense":[30],"reasoning,":[31],"they":[32],"struggle":[33],"with":[34],"geometric":[35,228],"spatial":[37],"understanding":[38],"required":[39],"for":[40,58],"pose":[41,78,135,170],"prediction.":[42],"In":[43],"this":[44],"paper,":[45],"we":[46,63],"propose":[47],"RobMRAG,":[48],"a":[49,65,82,89,118,177],"3D":[50,125,145],"Gaussian":[51,126],"Splatting-Enhanced":[52],"Retrieval-Augmented":[54],"Generation":[55],"(MRAG)":[56],"framework":[57],"zero-shot":[59,198],"manipulation.":[61],"Specifically,":[62],"construct":[64],"multi-source":[66],"knowledge":[68],"base":[69],"containing":[70,180],"object":[71,97,139,143],"contact":[72],"frames,":[73,76],"task":[74],"completion":[75],"parameters.":[79,171],"During":[80],"inference,":[81],"Hierarchical":[83],"Retrieval":[85],"module":[86,122],"first":[87],"employs":[88],"three-priority":[90],"hybrid":[91],"retrieval":[92],"strategy":[93],"find":[95],"task-relevant":[96],"prototypes,":[98],"then":[99],"selects":[100],"the":[101,129,134,137,141,153,161,165,168,189,196,201,209,220],"geometrically":[102],"closest":[103],"reference":[104,138],"example":[105],"based":[106,123],"on":[107,124,176],"pixel-level":[108],"similarity":[109],"Instance":[111],"Matching":[112],"Distance":[113],"(IMD).":[114],"We":[115],"further":[116],"introduce":[117],"3D-Aware":[119],"Pose":[120],"Refinement":[121],"Splatting":[127],"into":[128],"MRAG":[130],"framework,":[131],"which":[132],"aligns":[133],"target":[142],"in":[144],"space.":[146],"The":[147],"aligned":[148],"results":[149,214],"are":[150],"reprojected":[151],"onto":[152],"image":[154],"plane":[155],"used":[157],"as":[158],"input":[159],"MLLM":[162],"enhance":[164],"generation":[166],"final":[169],"Extensive":[172],"experiments":[173],"show":[174],"that":[175,216,233],"test":[178],"set":[179],"30":[181],"categories":[182],"household":[184],"objects,":[185],"our":[186],"method":[187],"improves":[188],"success":[190],"rate":[191],"by":[192,205],"7.76%":[193],"compared":[194,207],"best-performing":[197],"baseline":[199],"under":[200],"same":[202],"setting,":[203],"6.54%":[206],"state-of-the-art":[210],"supervised":[211],"baseline.":[212],"Our":[213],"validate":[215],"RobMRAG":[217],"effectively":[218],"bridges":[219],"gap":[221],"between":[222],"high-level":[223],"semantic":[224],"reasoning":[225],"low-level":[227],"execution,":[229],"enabling":[230],"systems":[232],"generalize":[234],"while":[238],"remaining":[239],"inherently":[240],"interpretable.":[241]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-04T00:00:00"}
